allow passing args to the example code

.gitignore

@@ -0,0 +1,2 @@
+build
+target

README.md

@@ -16,11 +16,17 @@ By way of a working example, OpenAI's Wikipedia corpus (25k documents) can be in
 
 Install RAFT (https://docs.rapids.ai/api/raft/stable/build/#installation)
 
+Download the dataset file [using this link](https://cdn.openai.com/API/examples/data/vector_database_wikipedia_articles_embedded.zip)
+
 Set the correct path for Raft in `cuda/CMakeLists.txt` file. Then, proceed to run the following (Wikipedia OpenAI benchmark):
 
     wget -c https://cdn.openai.com/API/examples/data/vector_database_wikipedia_articles_embedded.zip
     mvn package
-    java -jar lucene/target/cuvs-searcher-lucene-0.0.1-SNAPSHOT-jar-with-dependencies.jar
+    java -jar lucene/target/cuvs-searcher-lucene-0.0.1-SNAPSHOT-jar-with-dependencies.jar <datasetfile> <vector_index_column> <name_of_vector_field> <numDocs> <dimensions> <queryFile>
+
+    # Example
+    java -jar lucene/target/cuvs-searcher-lucene-0.0.1-SNAPSHOT-jar-with-dependencies.jar vector_database_wikipedia_articles_embedded.zip 5 content_vector 25000 768 query.txt
+
 
 ## Benchmarks
 

lucene/src/main/java/com/searchscale/lucene/vectorsearch/CuVSIndexSearcher.java

@@ -30,12 +30,12 @@ public CuVSIndexSearcher(IndexReader reader) {
     List<Integer> docIds = new ArrayList<>();
     List<float[]> dataVectors = new ArrayList<float[]>();
     try {
-      for (LeafReaderContext leaf: reader.leaves()) {
-        FloatVectorValues vectors = leaf.reader().getFloatVectorValues("content_vector");
+      for (LeafReaderContext leaf : reader.leaves()) {
+        FloatVectorValues vectors = leaf.reader().getFloatVectorValues(LuceneVectorSearchExample.vectorColName);
         DocIdSetIterator disi = FloatVectorValues.all(leaf.reader().maxDoc());
         for (int doc = disi.nextDoc(); doc != DocIdSetIterator.NO_MORE_DOCS; doc = disi.nextDoc()) {
           vectors.advance(doc);
-          docIds.add(leaf.docBase+doc);
+          docIds.add(leaf.docBase + doc);
           dataVectors.add(vectors.vectorValue().clone());
         }
       }
@@ -45,29 +45,31 @@ public CuVSIndexSearcher(IndexReader reader) {
     int numVectors = dataVectors.size();
     int dim = dataVectors.get(0).length;
     float[] singleDataVector = new float[numVectors * dim];
-    for (int i=0; i<numVectors; i++) {
-      for (int j=0; j<dim; j++) {
-        singleDataVector[i*dim + j] = dataVectors.get(i)[j];
+    for (int i = 0; i < numVectors; i++) {
+      for (int j = 0; j < dim; j++) {
+        singleDataVector[i * dim + j] = dataVectors.get(i)[j];
       }
     }
     int docIdsArr[] = new int[docIds.size()];
-    for (int i=0; i<docIdsArr.length; i++) docIdsArr[i] = docIds.get(i);
-    System.out.println("Time taken for copying data from IndexReader to arrays for C++: " + (System.currentTimeMillis()-startTime));
+    for (int i = 0; i < docIdsArr.length; i++)
+      docIdsArr[i] = docIds.get(i);
+    System.out.println(
+        "Time taken for copying data from IndexReader to arrays for C++: " + (System.currentTimeMillis() - startTime));
     startTime = System.currentTimeMillis();
     jni.initIndex(docIdsArr, singleDataVector, docIdsArr.length, dataVectors.get(0).length);
-    System.out.println("Time taken for index building: " + (System.currentTimeMillis()-startTime));
+    System.out.println("Time taken for index building: " + (System.currentTimeMillis() - startTime));
   }
 
   @Override
   public TopDocs search(Query query, int n) throws IOException {
     KnnFloatVectorQuery knnQuery = (KnnFloatVectorQuery) query;
     Object results = jni.getTopK(knnQuery.getTargetCopy(), knnQuery.getK());
-    ByteBuffer buf = ((ByteBuffer)results).order(ByteOrder.nativeOrder());
+    ByteBuffer buf = ((ByteBuffer) results).order(ByteOrder.nativeOrder());
     int N = buf.limit() / 8;
     ScoreDoc scoreDocs[] = new ScoreDoc[N];
-    for (int i=0; i<N; i++) {
-      float score = buf.getFloat((i)*4);
-      int id = buf.getInt((N+i)*4);
+    for (int i = 0; i < N; i++) {
+      float score = buf.getFloat((i) * 4);
+      int id = buf.getInt((N + i) * 4);
       scoreDocs[i] = new ScoreDoc(id, score);
     }
     return new TopDocs(new TotalHits(N, TotalHits.Relation.EQUAL_TO), scoreDocs);

lucene/src/main/java/com/searchscale/lucene/vectorsearch/LuceneVectorSearchExample.java

@@ -1,5 +1,7 @@
 package com.searchscale.lucene.vectorsearch;
+
 import java.io.File;
+import java.io.FileInputStream;
 import java.io.IOException;
 import java.io.InputStreamReader;
 import java.util.Arrays;
@@ -38,55 +40,84 @@
 
 public class LuceneVectorSearchExample {
 
-  public static int DIMENSIONS = 1536;
-
-  public static void main(String[] args) {
+  public static String vectorColName = null;
+
+  public static void main(String[] args) throws Exception {
+
+    // [0] Parse Args
+
+    String datasetFile = args[0];
+    int indexOfVector = Integer.valueOf(args[1]);
+    vectorColName = args[2];
+    int numDocs = Integer.valueOf(args[3]);
+    int dims = Integer.valueOf(args[4]);
+    String queryFile = args[5];
+    System.out.println("Dataset file used is: " + datasetFile);
+    System.out.println("Index of vector field is: " + indexOfVector);
+    System.out.println("Name of the vector field is: " + vectorColName);
+    System.out.println("Number of documents to be indexed are: " + numDocs);
+    System.out.println("Number of dimensions are: " + dims);
+    System.out.println("Query file used is: " + queryFile);
+
     // [1] Setup the index
     Directory index = new ByteBuffersDirectory();
-    Lucene99Codec knnVectorsCodec = getCodec(DIMENSIONS);
+    Lucene99Codec knnVectorsCodec = getCodec(dims);
     IndexWriterConfig config = new IndexWriterConfig(new StandardAnalyzer()).setCodec(knnVectorsCodec);
 
     // [2] Index
     long startTime = System.currentTimeMillis();
-    try (ZipFile zip = new ZipFile("vector_database_wikipedia_articles_embedded.zip");
-        IndexWriter writer = new IndexWriter(index, config)) {
-      CSVReader reader = new CSVReader(new InputStreamReader(zip.getInputStream(zip.entries().nextElement())));
+    {
+      InputStreamReader isr = null;
+      IndexWriter writer = new IndexWriter(index, config);
+      if (datasetFile.endsWith(".zip")) {
+        ZipFile zip = new ZipFile(datasetFile);
+        isr = new InputStreamReader(zip.getInputStream(zip.entries().nextElement()));
+      } else {
+        isr = new InputStreamReader(new FileInputStream(datasetFile));
+      }
+
+      CSVReader reader = new CSVReader(isr);
       String[] line;
       int count = 0;
       while ((line = reader.readNext()) != null) {
-        if ((count++) == 0) continue; // skip the first line of the file, it is a header
+        if ((count++) == 0)
+          continue; // skip the first line of the file, it is a header
         Document doc = new Document();
-        doc.add(new StringField("id", ""+(count-2), Field.Store.YES));
+        doc.add(new StringField("id", "" + (count - 2), Field.Store.YES));
         doc.add(new StringField("url", line[1], Field.Store.YES));
         doc.add(new StringField("title", line[2], Field.Store.YES));
         doc.add(new TextField("text", line[3], Field.Store.YES));
-        float[] contentVector = reduceDimensionVector(parseFloatArrayFromStringArray(line[5]), DIMENSIONS);
-        doc.add(new KnnFloatVectorField("content_vector", contentVector, VectorSimilarityFunction.EUCLIDEAN));
+        float[] contentVector = reduceDimensionVector(parseFloatArrayFromStringArray(line[5]), dims);
+        doc.add(new KnnFloatVectorField(vectorColName, contentVector, VectorSimilarityFunction.EUCLIDEAN));
         doc.add(new StringField("vector_id", line[6], Field.Store.YES));
-        if (count % 500 == 0) writer.commit();
-        if (count % 5000 == 0) System.out.println(count + " docs indexed ...");
+
+        if (count % 500 == 0)
+          writer.commit();
+        if (count % 5000 == 0)
+          System.out.println(count + " docs indexed ...");
         writer.addDocument(doc);
+        if (count == numDocs)
+          break;
       }
       writer.commit();
-    } catch (Exception e) {
-      e.printStackTrace();
     }
-    System.out.println("Time taken for index building (end to end): " + (System.currentTimeMillis()-startTime));
+
+    System.out.println("Time taken for index building (end to end): " + (System.currentTimeMillis() - startTime));
 
     // [3] Query
     try (IndexReader reader = DirectoryReader.open(index)) {
       IndexSearcher searcher = new CuVSIndexSearcher(reader);
-      for (String line: FileUtils.readFileToString(new File("query.txt"), "UTF-8").split("\n")) {
-        float queryVector[] = reduceDimensionVector(parseFloatArrayFromStringArray(line), DIMENSIONS);
-        Query query = new KnnFloatVectorQuery("content_vector", queryVector, 5);
+      for (String line : FileUtils.readFileToString(new File(queryFile), "UTF-8").split("\n")) {
+        float queryVector[] = reduceDimensionVector(parseFloatArrayFromStringArray(line), dims);
+        Query query = new KnnFloatVectorQuery(vectorColName, queryVector, 5);
         startTime = System.currentTimeMillis();
-        TopDocs topDocs = searcher.search(query, ((KnnFloatVectorQuery)query).getK());
-        System.out.println("Time taken for searching (end to end): " + (System.currentTimeMillis()-startTime));
+        TopDocs topDocs = searcher.search(query, ((KnnFloatVectorQuery) query).getK());
+        System.out.println("Time taken for searching (end to end): " + (System.currentTimeMillis() - startTime));
         ScoreDoc[] hits = topDocs.scoreDocs;
         System.out.println("Found " + hits.length + " hits.");
-        for (ScoreDoc hit: hits) {
+        for (ScoreDoc hit : hits) {
           Document d = searcher.storedFields().document(hit.doc);
-          System.out.println("DocID: " + hit.doc + ", Score: " + hit.score + ", Title: " + d.get("title"));
+          System.out.println("DocID: " + hit.doc + ", Score: " + hit.score);
         }
       }
     } catch (Exception e) {
@@ -95,7 +126,8 @@ public static void main(String[] args) {
   }
 
   private static Lucene99Codec getCodec(int dimensions) {
-    if (dimensions <= 1024) return new Lucene99Codec(Mode.BEST_SPEED);
+    if (dimensions <= 1024)
+      return new Lucene99Codec(Mode.BEST_SPEED);
     Lucene99Codec knnVectorsCodec = new Lucene99Codec(Mode.BEST_SPEED) {
       @Override
       public KnnVectorsFormat getKnnVectorsFormatForField(String field) {
@@ -109,14 +141,15 @@ public KnnVectorsFormat getKnnVectorsFormatForField(String field) {
   }
 
   private static float[] parseFloatArrayFromStringArray(String str) {
-    float[] titleVector = ArrayUtils.toPrimitive(Arrays.stream(str.replace("[", "").replace("]", "").
-        split(", ")).map(Float::valueOf).toArray(Float[]::new));
+    float[] titleVector = ArrayUtils.toPrimitive(
+        Arrays.stream(str.replace("[", "").replace("]", "").split(", ")).map(Float::valueOf).toArray(Float[]::new));
     return titleVector;
   }
 
   public static float[] reduceDimensionVector(float[] vector, int dim) {
     float out[] = new float[dim];
-    for (int i=0; i<dim && i<vector.length; i++) out[i] = vector[i];
+    for (int i = 0; i < dim && i < vector.length; i++)
+      out[i] = vector[i];
     return out;
   }